Re: Spark Streaming + Kudu

[Mike Percy]

Have you considered checking your session error count or pending errors in
your while loop every so often? Can you identify where your code is hanging
when the connection is lost (what line)?

Mike

On Mon, Mar 5, 2018 at 9:08 PM, Ravi Kanth  wrote:

> In addition to my previous comment, I raised a support ticket for this
> issue with Cloudera and one of the support person mentioned below,
>
> *"Thank you for clarifying, The exceptions are logged but not re-thrown to
> an upper layer, so that explains why the Spark application is not aware of
> the underlying error."*
>
> On 5 March 2018 at 21:02, Ravi Kanth  wrote:
>
>> Mike,
>>
>> Thanks for the information. But, once the connection to any of the Kudu
>> servers is lost then there is no way I can have a control on the
>> KuduSession object and so with getPendingErrors(). The KuduClient in this
>> case is becoming a zombie and never returned back till the connection is
>> properly established. I tried doing all that you have suggested with no
>> luck. Attaching my KuduClient code.
>>
>> package org.dwh.streaming.kudu.sparkkudustreaming;
>>
>> import java.util.HashMap;
>> import java.util.Iterator;
>> import java.util.Map;
>> import org.apache.hadoop.util.ShutdownHookManager;
>> import org.apache.kudu.client.*;
>> import org.apache.spark.api.java.JavaRDD;
>> import org.slf4j.Logger;
>> import org.slf4j.LoggerFactory;
>> import org.dwh.streaming.kudu.sparkkudustreaming.constants.SpecialN
>> ullConstants;
>>
>> public class KuduProcess {
>> private static Logger logger = LoggerFactory.getLogger(KuduPr
>> ocess.class);
>> private KuduTable table;
>> private KuduSession session;
>>
>> public static void upsertKudu(JavaRDD> rdd, String
>> host, String tableName) {
>> rdd.foreachPartition(iterator -> {
>> RowErrorsAndOverflowStatus errors = upsertOpIterator(iterator, tableName,
>> host);
>> int errorCount = errors.getRowErrors().length;
>> if(errorCount > 0){
>> throw new RuntimeException("Failed to write " + errorCount + " messages
>> into Kudu");
>> }
>> });
>> }
>> private static RowErrorsAndOverflowStatus 
>> upsertOpIterator(Iterator> Object>> iter, String tableName, String host) {
>> try {
>> AsyncKuduClient asyncClient = KuduConnection.getAsyncClient(host);
>> KuduClient client = asyncClient.syncClient();
>> table = client.openTable(tableName);
>> session = client.newSession();
>> session.setFlushMode(SessionConfiguration.FlushMode.AUTO_FLU
>> SH_BACKGROUND);
>> while (iter.hasNext()) {
>> upsertOp(iter.next());
>> }
>> } catch (KuduException e) {
>> logger.error("Exception in upsertOpIterator method", e);
>> }
>> finally{
>> try {
>> session.close();
>> } catch (KuduException e) {
>> logger.error("Exception in Connection close", e);
>> }
>> }
>> return session.getPendingErrors();-> Once,
>> the connection is lost, this part of the code never gets called and the
>> Spark job will keep on running and processing the records while the
>> KuduClient is trying to connect to Kudu. Meanwhile, we are loosing all the
>> records.
>> }
>> public static void upsertOp(Map formattedMap) {
>> if (formattedMap.size() != 0) {
>> try {
>> Upsert upsert = table.newUpsert();
>> PartialRow row = upsert.getRow();
>> for (Map.Entry entry : formattedMap.entrySet()) {
>> if (entry.getValue().getClass().equals(String.class)) {
>> if (entry.getValue().equals(SpecialNullConstants.specialStringNull))
>> row.setNull(entry.getKey());
>> else
>> row.addString(entry.getKey(), (String) entry.getValue());
>> } else if (entry.getValue().getClass().equals(Long.class)) {
>> if (entry.getValue().equals(SpecialNullConstants.specialLongNull))
>> row.setNull(entry.getKey());
>> else
>> row.addLong(entry.getKey(), (Long) entry.getValue());
>> } else if (entry.getValue().getClass().equals(Integer.class)) {
>> if (entry.getValue().equals(SpecialNullConstants.specialIntNull))
>> row.setNull(entry.getKey());
>> else
>> row.addInt(entry.getKey(), (Integer) entry.getValue());
>> }
>> }
>>
>> session.apply(upsert);
>> } catch (Exception e) {
>> logger.error("Exception during upsert:", e);
>> }
>> }
>> }
>> }
>> class KuduConnection {
>> private static Logger logger = LoggerFactory.getLogger(KuduCo
>> nnection.class);
>> private static Map asyncCache = new HashMap<>();
>> private static int ShutdownHookPriority = 100;
>>
>> static AsyncKuduClient getAsyncClient(String kuduMaster) {
>> if (!asyncCache.containsKey(kuduMaster)) {
>> AsyncKuduClient asyncClient = new AsyncKuduClient.AsyncKuduClien
>> tBuilder(kuduMaster).build();
>> ShutdownHookManager.get().addShutdownHook(new Runnable() {
>> @Override
>> public void run() {
>> try {
>> asyncClient.close();
>> } catch (Exception e) {
>> logger.error("Exception closing async client", e);
>> }
>> }
>> }, ShutdownHookPriority);
>> asyncCache.put(kuduMaster, asyncClient);
>> }
>> return asyncCache.get(kuduMaster);
>> }
>> }
>>
>>
>>
>> Thanks,
>> Ravi
>>
>> On 5 March 2018 at 16:20, Mike Percy  wrote:
>>
>>> Hi Ravi, it would be helpf

Re: Spark Streaming + Kudu

[Ravi Kanth]

In addition to my previous comment, I raised a support ticket for this
issue with Cloudera and one of the support person mentioned below,

*"Thank you for clarifying, The exceptions are logged but not re-thrown to
an upper layer, so that explains why the Spark application is not aware of
the underlying error."*

On 5 March 2018 at 21:02, Ravi Kanth  wrote:

> Mike,
>
> Thanks for the information. But, once the connection to any of the Kudu
> servers is lost then there is no way I can have a control on the
> KuduSession object and so with getPendingErrors(). The KuduClient in this
> case is becoming a zombie and never returned back till the connection is
> properly established. I tried doing all that you have suggested with no
> luck. Attaching my KuduClient code.
>
> package org.dwh.streaming.kudu.sparkkudustreaming;
>
> import java.util.HashMap;
> import java.util.Iterator;
> import java.util.Map;
> import org.apache.hadoop.util.ShutdownHookManager;
> import org.apache.kudu.client.*;
> import org.apache.spark.api.java.JavaRDD;
> import org.slf4j.Logger;
> import org.slf4j.LoggerFactory;
> import org.dwh.streaming.kudu.sparkkudustreaming.constants.
> SpecialNullConstants;
>
> public class KuduProcess {
> private static Logger logger = LoggerFactory.getLogger(KuduProcess.class);
> private KuduTable table;
> private KuduSession session;
>
> public static void upsertKudu(JavaRDD> rdd, String
> host, String tableName) {
> rdd.foreachPartition(iterator -> {
> RowErrorsAndOverflowStatus errors = upsertOpIterator(iterator, tableName,
> host);
> int errorCount = errors.getRowErrors().length;
> if(errorCount > 0){
> throw new RuntimeException("Failed to write " + errorCount + " messages
> into Kudu");
> }
> });
> }
> private static RowErrorsAndOverflowStatus 
> upsertOpIterator(Iterator Object>> iter, String tableName, String host) {
> try {
> AsyncKuduClient asyncClient = KuduConnection.getAsyncClient(host);
> KuduClient client = asyncClient.syncClient();
> table = client.openTable(tableName);
> session = client.newSession();
> session.setFlushMode(SessionConfiguration.FlushMode.AUTO_FLUSH_
> BACKGROUND);
> while (iter.hasNext()) {
> upsertOp(iter.next());
> }
> } catch (KuduException e) {
> logger.error("Exception in upsertOpIterator method", e);
> }
> finally{
> try {
> session.close();
> } catch (KuduException e) {
> logger.error("Exception in Connection close", e);
> }
> }
> return session.getPendingErrors();-> Once,
> the connection is lost, this part of the code never gets called and the
> Spark job will keep on running and processing the records while the
> KuduClient is trying to connect to Kudu. Meanwhile, we are loosing all the
> records.
> }
> public static void upsertOp(Map formattedMap) {
> if (formattedMap.size() != 0) {
> try {
> Upsert upsert = table.newUpsert();
> PartialRow row = upsert.getRow();
> for (Map.Entry entry : formattedMap.entrySet()) {
> if (entry.getValue().getClass().equals(String.class)) {
> if (entry.getValue().equals(SpecialNullConstants.specialStringNull))
> row.setNull(entry.getKey());
> else
> row.addString(entry.getKey(), (String) entry.getValue());
> } else if (entry.getValue().getClass().equals(Long.class)) {
> if (entry.getValue().equals(SpecialNullConstants.specialLongNull))
> row.setNull(entry.getKey());
> else
> row.addLong(entry.getKey(), (Long) entry.getValue());
> } else if (entry.getValue().getClass().equals(Integer.class)) {
> if (entry.getValue().equals(SpecialNullConstants.specialIntNull))
> row.setNull(entry.getKey());
> else
> row.addInt(entry.getKey(), (Integer) entry.getValue());
> }
> }
>
> session.apply(upsert);
> } catch (Exception e) {
> logger.error("Exception during upsert:", e);
> }
> }
> }
> }
> class KuduConnection {
> private static Logger logger = LoggerFactory.getLogger(
> KuduConnection.class);
> private static Map asyncCache = new HashMap<>();
> private static int ShutdownHookPriority = 100;
>
> static AsyncKuduClient getAsyncClient(String kuduMaster) {
> if (!asyncCache.containsKey(kuduMaster)) {
> AsyncKuduClient asyncClient = new AsyncKuduClient.AsyncKuduClientBuilder(
> kuduMaster).build();
> ShutdownHookManager.get().addShutdownHook(new Runnable() {
> @Override
> public void run() {
> try {
> asyncClient.close();
> } catch (Exception e) {
> logger.error("Exception closing async client", e);
> }
> }
> }, ShutdownHookPriority);
> asyncCache.put(kuduMaster, asyncClient);
> }
> return asyncCache.get(kuduMaster);
> }
> }
>
>
>
> Thanks,
> Ravi
>
> On 5 March 2018 at 16:20, Mike Percy  wrote:
>
>> Hi Ravi, it would be helpful if you could attach what you are getting
>> back from getPendingErrors() -- perhaps from dumping RowError.toString()
>> from items in the returned array -- and indicate what you were hoping to
>> get back. Note that a RowError can also return to you the Operation
>> 
>> that you used to generate the

Re: Spark Streaming + Kudu

[Ravi Kanth]

Mike,

Thanks for the information. But, once the connection to any of the Kudu
servers is lost then there is no way I can have a control on the
KuduSession object and so with getPendingErrors(). The KuduClient in this
case is becoming a zombie and never returned back till the connection is
properly established. I tried doing all that you have suggested with no
luck. Attaching my KuduClient code.

package org.dwh.streaming.kudu.sparkkudustreaming;

import java.util.HashMap;
import java.util.Iterator;
import java.util.Map;
import org.apache.hadoop.util.ShutdownHookManager;
import org.apache.kudu.client.*;
import org.apache.spark.api.java.JavaRDD;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import
org.dwh.streaming.kudu.sparkkudustreaming.constants.SpecialNullConstants;

public class KuduProcess {
private static Logger logger = LoggerFactory.getLogger(KuduProcess.class);
private KuduTable table;
private KuduSession session;

public static void upsertKudu(JavaRDD> rdd, String
host, String tableName) {
rdd.foreachPartition(iterator -> {
RowErrorsAndOverflowStatus errors = upsertOpIterator(iterator, tableName,
host);
int errorCount = errors.getRowErrors().length;
if(errorCount > 0){
throw new RuntimeException("Failed to write " + errorCount + " messages
into Kudu");
}
});
}
private static RowErrorsAndOverflowStatus
upsertOpIterator(Iterator> iter, String tableName,
String host) {
try {
AsyncKuduClient asyncClient = KuduConnection.getAsyncClient(host);
KuduClient client = asyncClient.syncClient();
table = client.openTable(tableName);
session = client.newSession();
session.setFlushMode(SessionConfiguration.FlushMode.AUTO_FLUSH_BACKGROUND);
while (iter.hasNext()) {
upsertOp(iter.next());
}
} catch (KuduException e) {
logger.error("Exception in upsertOpIterator method", e);
}
finally{
try {
session.close();
} catch (KuduException e) {
logger.error("Exception in Connection close", e);
}
}
return session.getPendingErrors();-> Once, the
connection is lost, this part of the code never gets called and the Spark
job will keep on running and processing the records while the KuduClient is
trying to connect to Kudu. Meanwhile, we are loosing all the records.
}
public static void upsertOp(Map formattedMap) {
if (formattedMap.size() != 0) {
try {
Upsert upsert = table.newUpsert();
PartialRow row = upsert.getRow();
for (Map.Entry entry : formattedMap.entrySet()) {
if (entry.getValue().getClass().equals(String.class)) {
if (entry.getValue().equals(SpecialNullConstants.specialStringNull))
row.setNull(entry.getKey());
else
row.addString(entry.getKey(), (String) entry.getValue());
} else if (entry.getValue().getClass().equals(Long.class)) {
if (entry.getValue().equals(SpecialNullConstants.specialLongNull))
row.setNull(entry.getKey());
else
row.addLong(entry.getKey(), (Long) entry.getValue());
} else if (entry.getValue().getClass().equals(Integer.class)) {
if (entry.getValue().equals(SpecialNullConstants.specialIntNull))
row.setNull(entry.getKey());
else
row.addInt(entry.getKey(), (Integer) entry.getValue());
}
}

session.apply(upsert);
} catch (Exception e) {
logger.error("Exception during upsert:", e);
}
}
}
}
class KuduConnection {
private static Logger logger =
LoggerFactory.getLogger(KuduConnection.class);
private static Map asyncCache = new HashMap<>();
private static int ShutdownHookPriority = 100;

static AsyncKuduClient getAsyncClient(String kuduMaster) {
if (!asyncCache.containsKey(kuduMaster)) {
AsyncKuduClient asyncClient = new
AsyncKuduClient.AsyncKuduClientBuilder(kuduMaster).build();
ShutdownHookManager.get().addShutdownHook(new Runnable() {
@Override
public void run() {
try {
asyncClient.close();
} catch (Exception e) {
logger.error("Exception closing async client", e);
}
}
}, ShutdownHookPriority);
asyncCache.put(kuduMaster, asyncClient);
}
return asyncCache.get(kuduMaster);
}
}



Thanks,
Ravi

On 5 March 2018 at 16:20, Mike Percy  wrote:

> Hi Ravi, it would be helpful if you could attach what you are getting back
> from getPendingErrors() -- perhaps from dumping RowError.toString() from
> items in the returned array -- and indicate what you were hoping to get
> back. Note that a RowError can also return to you the Operation
> 
> that you used to generate the write. From the Operation, you can get the
> original PartialRow
> 
> object, which should be able to identify the affected row that the write
> failed for. Does that help?
>
> Since you are using the Kudu client directly, Spark is not involved from
> the Kudu perspective, so you will need to deal with Spark on your own in
> that case.
>
> Mike
>
> On Mon, Mar 5, 2018 at 1:59 PM, Ravi Kanth 
> wrote:
>
>> Hi Mike,
>>
>> Thanks for the reply. Yes, I am using AUTO_FLUSH_BACKGROUND.
>>
>> So, I am trying to use Kudu Client API to perform 

Re: Spark Streaming + Kudu

[Mike Percy]

Hi Ravi, it would be helpful if you could attach what you are getting back
from getPendingErrors() -- perhaps from dumping RowError.toString() from
items in the returned array -- and indicate what you were hoping to get
back. Note that a RowError can also return to you the Operation

that you used to generate the write. From the Operation, you can get the
original PartialRow

object, which should be able to identify the affected row that the write
failed for. Does that help?

Since you are using the Kudu client directly, Spark is not involved from
the Kudu perspective, so you will need to deal with Spark on your own in
that case.

Mike

On Mon, Mar 5, 2018 at 1:59 PM, Ravi Kanth  wrote:

> Hi Mike,
>
> Thanks for the reply. Yes, I am using AUTO_FLUSH_BACKGROUND.
>
> So, I am trying to use Kudu Client API to perform UPSERT into Kudu and I
> integrated this with Spark. I am trying to test a case where in if any of
> Kudu server fails. So, in this case, if there is any problem in writing,
> getPendingErrors() should give me a way to handle these errors so that I
> can successfully terminate my Spark Job. This is what I am trying to do.
>
> But, I am not able to get a hold of the exceptions being thrown from with
> in the KuduClient when retrying to connect to Tablet Server. My
> getPendingErrors is not getting ahold of these exceptions.
>
> Let me know if you need more clarification. I can post some Snippets.
>
> Thanks,
> Ravi
>
> On 5 March 2018 at 13:18, Mike Percy  wrote:
>
>> Hi Ravi, are you using AUTO_FLUSH_BACKGROUND
>> ?
>> You mention that you are trying to use getPendingErrors()
>> 
>>  but
>> it sounds like it's not working for you -- can you be more specific about
>> what you expect and what you are observing?
>>
>> Thanks,
>> Mike
>>
>>
>>
>> On Mon, Feb 26, 2018 at 8:04 PM, Ravi Kanth 
>> wrote:
>>
>>> Thank Clifford. We are running Kudu 1.4 version. Till date we didn't see
>>> any issues in production and we are not losing tablet servers. But, as part
>>> of testing I have to generate few unforeseen cases to analyse the
>>> application performance. One among that is bringing down the tablet server
>>> or master server intentionally during which I observed the loss of records.
>>> Just wanted to test cases out of the happy path here. Once again thanks for
>>> taking time to respond to me.
>>>
>>> - Ravi
>>>
>>> On 26 February 2018 at 19:58, Clifford Resnick 
>>> wrote:
>>>
 I'll have to get back to you on the code bits, but I'm pretty sure
 we're doing simple sync batching. We're not in production yet, but after
 some months of development I haven't seen any failures, even when pushing
 load doing multiple years' backfill. I think the real question is why are
 you losing tablet servers? The only instability we ever had with Kudu was
 when it had that weird ntp sync issue that was fixed I think for 1.6. What
 version are you running?

 Anyway I would think that infinite loop should be catchable somewhere.
 Our pipeline is set to fail/retry with Flink snapshots. I imagine there is
 similar with Spark. Sorry I cant be of more help!



 On Feb 26, 2018 9:10 PM, Ravi Kanth  wrote:

 Cliff,

 Thanks for the response. Well, I do agree that its simple and seamless.
 In my case, I am able to upsert ~25000 events/sec into Kudu. But, I am
 facing the problem when any of the Kudu Tablet or master server is down. I
 am not able to get a hold of the exception from client. The client is going
 into an infinite loop trying to connect to Kudu. Meanwhile, I am loosing my
 records. I tried handling the errors through getPendingErrors() but still
 it is helpless. I am using AsyncKuduClient to establish the connection and
 retrieving the syncClient from the Async to open the session and table. Any
 help?

 Thanks,
 Ravi

 On 26 February 2018 at 18:00, Cliff Resnick  wrote:

 While I can't speak for Spark, we do use the client API from Flink
 streaming and it's simple and seamless. It's especially nice if you require
 an Upsert semantic.

 On Feb 26, 2018 7:51 PM, "Ravi Kanth"  wrote:

 Hi,

 Anyone using Spark Streaming to ingest data into Kudu and using Kudu
 Client API to do so rather than the traditional KuduContext API? I am stuck
 at a point and couldn't find a solution.

 Thanks,
 Ravi




>>>
>>
>

Re: Spark Streaming + Kudu

[Ravi Kanth]

Hi Mike,

Thanks for the reply. Yes, I am using AUTO_FLUSH_BACKGROUND.

So, I am trying to use Kudu Client API to perform UPSERT into Kudu and I
integrated this with Spark. I am trying to test a case where in if any of
Kudu server fails. So, in this case, if there is any problem in writing,
getPendingErrors() should give me a way to handle these errors so that I
can successfully terminate my Spark Job. This is what I am trying to do.

But, I am not able to get a hold of the exceptions being thrown from with
in the KuduClient when retrying to connect to Tablet Server. My
getPendingErrors is not getting ahold of these exceptions.

Let me know if you need more clarification. I can post some Snippets.

Thanks,
Ravi

On 5 March 2018 at 13:18, Mike Percy  wrote:

> Hi Ravi, are you using AUTO_FLUSH_BACKGROUND
> ?
> You mention that you are trying to use getPendingErrors()
> 
>  but
> it sounds like it's not working for you -- can you be more specific about
> what you expect and what you are observing?
>
> Thanks,
> Mike
>
>
>
> On Mon, Feb 26, 2018 at 8:04 PM, Ravi Kanth 
> wrote:
>
>> Thank Clifford. We are running Kudu 1.4 version. Till date we didn't see
>> any issues in production and we are not losing tablet servers. But, as part
>> of testing I have to generate few unforeseen cases to analyse the
>> application performance. One among that is bringing down the tablet server
>> or master server intentionally during which I observed the loss of records.
>> Just wanted to test cases out of the happy path here. Once again thanks for
>> taking time to respond to me.
>>
>> - Ravi
>>
>> On 26 February 2018 at 19:58, Clifford Resnick 
>> wrote:
>>
>>> I'll have to get back to you on the code bits, but I'm pretty sure we're
>>> doing simple sync batching. We're not in production yet, but after some
>>> months of development I haven't seen any failures, even when pushing load
>>> doing multiple years' backfill. I think the real question is why are you
>>> losing tablet servers? The only instability we ever had with Kudu was when
>>> it had that weird ntp sync issue that was fixed I think for 1.6. What
>>> version are you running?
>>>
>>> Anyway I would think that infinite loop should be catchable somewhere.
>>> Our pipeline is set to fail/retry with Flink snapshots. I imagine there is
>>> similar with Spark. Sorry I cant be of more help!
>>>
>>>
>>>
>>> On Feb 26, 2018 9:10 PM, Ravi Kanth  wrote:
>>>
>>> Cliff,
>>>
>>> Thanks for the response. Well, I do agree that its simple and seamless.
>>> In my case, I am able to upsert ~25000 events/sec into Kudu. But, I am
>>> facing the problem when any of the Kudu Tablet or master server is down. I
>>> am not able to get a hold of the exception from client. The client is going
>>> into an infinite loop trying to connect to Kudu. Meanwhile, I am loosing my
>>> records. I tried handling the errors through getPendingErrors() but still
>>> it is helpless. I am using AsyncKuduClient to establish the connection and
>>> retrieving the syncClient from the Async to open the session and table. Any
>>> help?
>>>
>>> Thanks,
>>> Ravi
>>>
>>> On 26 February 2018 at 18:00, Cliff Resnick  wrote:
>>>
>>> While I can't speak for Spark, we do use the client API from Flink
>>> streaming and it's simple and seamless. It's especially nice if you require
>>> an Upsert semantic.
>>>
>>> On Feb 26, 2018 7:51 PM, "Ravi Kanth"  wrote:
>>>
>>> Hi,
>>>
>>> Anyone using Spark Streaming to ingest data into Kudu and using Kudu
>>> Client API to do so rather than the traditional KuduContext API? I am stuck
>>> at a point and couldn't find a solution.
>>>
>>> Thanks,
>>> Ravi
>>>
>>>
>>>
>>>
>>
>

Re: Spark Streaming + Kudu

[Mike Percy]

Hi Ravi, are you using AUTO_FLUSH_BACKGROUND
?
You mention that you are trying to use getPendingErrors()

but
it sounds like it's not working for you -- can you be more specific about
what you expect and what you are observing?

Thanks,
Mike



On Mon, Feb 26, 2018 at 8:04 PM, Ravi Kanth  wrote:

> Thank Clifford. We are running Kudu 1.4 version. Till date we didn't see
> any issues in production and we are not losing tablet servers. But, as part
> of testing I have to generate few unforeseen cases to analyse the
> application performance. One among that is bringing down the tablet server
> or master server intentionally during which I observed the loss of records.
> Just wanted to test cases out of the happy path here. Once again thanks for
> taking time to respond to me.
>
> - Ravi
>
> On 26 February 2018 at 19:58, Clifford Resnick 
> wrote:
>
>> I'll have to get back to you on the code bits, but I'm pretty sure we're
>> doing simple sync batching. We're not in production yet, but after some
>> months of development I haven't seen any failures, even when pushing load
>> doing multiple years' backfill. I think the real question is why are you
>> losing tablet servers? The only instability we ever had with Kudu was when
>> it had that weird ntp sync issue that was fixed I think for 1.6. What
>> version are you running?
>>
>> Anyway I would think that infinite loop should be catchable somewhere.
>> Our pipeline is set to fail/retry with Flink snapshots. I imagine there is
>> similar with Spark. Sorry I cant be of more help!
>>
>>
>>
>> On Feb 26, 2018 9:10 PM, Ravi Kanth  wrote:
>>
>> Cliff,
>>
>> Thanks for the response. Well, I do agree that its simple and seamless.
>> In my case, I am able to upsert ~25000 events/sec into Kudu. But, I am
>> facing the problem when any of the Kudu Tablet or master server is down. I
>> am not able to get a hold of the exception from client. The client is going
>> into an infinite loop trying to connect to Kudu. Meanwhile, I am loosing my
>> records. I tried handling the errors through getPendingErrors() but still
>> it is helpless. I am using AsyncKuduClient to establish the connection and
>> retrieving the syncClient from the Async to open the session and table. Any
>> help?
>>
>> Thanks,
>> Ravi
>>
>> On 26 February 2018 at 18:00, Cliff Resnick  wrote:
>>
>> While I can't speak for Spark, we do use the client API from Flink
>> streaming and it's simple and seamless. It's especially nice if you require
>> an Upsert semantic.
>>
>> On Feb 26, 2018 7:51 PM, "Ravi Kanth"  wrote:
>>
>> Hi,
>>
>> Anyone using Spark Streaming to ingest data into Kudu and using Kudu
>> Client API to do so rather than the traditional KuduContext API? I am stuck
>> at a point and couldn't find a solution.
>>
>> Thanks,
>> Ravi
>>
>>
>>
>>
>

Re: Kudu as a Graphite backend

[Todd Lipcon]

Hey Mark,

Yea, I wrote the original Graphite integration in the samples repo several
years ago (prior to Kudu 0.5 even), but it was more of a quick prototype in
order to have a demo of the Python client rather than something meant to be
used in a production scenario. Of course with some work it could probably
be updated and made more "real".

You may also be interested in the 'kudu-ts' project that Dan Burkert
started: https://github.com/danburkert/kudu-ts

It provides an OpenTSDB-compatible interface on top of Kudu. Unfortunately
it's also somewhat incomplete but could provide a decent starting point for
a time series workload.

It would be great if you wanted to contribute to either the graphite-kudu
integration or kudu-ts. Neither is getting the love they deserve right now.

-Todd

On Mon, Mar 5, 2018 at 7:38 AM, Paul Brannan 
wrote:

> Do you want to use kudu as a backend for carbon (i.e. have graphite/carbon
> receive metrics and write them to kudu), or do you want to use graphite-web
> as a frontend for timeseries you already have in kudu?  Both are mostly
> straightforward; see e.g. https://github.com/criteo/
> biggraphite/tree/master/biggraphite/plugins for an example of each.
> AFAICT the examples (https://github.com/cloudera/
> kudu-examples/tree/master/python/graphite-kudu) are just a graphite-web
> finder; you'd still need a carbon backend for storage, unless you insert
> the data through a different mechanism.
>
> On Mon, Mar 5, 2018 at 6:15 AM, Mark Meyer  wrote:
>
>> Hi List,
>> has anybody experiences running Kudu as a Graphite backend in production?
>> I've been looking at the samples repository, but have been unsure,
>> primarily because of the 'samples' tag associated with the code.
>>
>> Best, Mark
>>
>> --
>> Mark Meyer
>> Systems Engineer
>> mark.me...@smaato.com
>> Smaato Inc.
>> San Francisco – New York – Hamburg – Singapore
>> www.smaato.com
>>
>> Valentinskamp 70
>> ,
>> Emporio, 19th Floor
>> 20355 Hamburg
>> T: ­0049 (40) 3480 949 0
>> F: 0049 (40) 492 19 055
>>
>> The information contained in this communication may be CONFIDENTIAL and
>> is intended only for the use of the recipient(s) named above. If you are
>> not the intended recipient, you are hereby notified that any dissemination,
>> distribution, or copying of this communication, or any of its contents, is
>> strictly prohibited. If you have received this communication in error,
>> please notify the sender and delete/destroy the original message and any
>> copy of it from your computer or paper files.
>>
>
>


-- 
Todd Lipcon
Software Engineer, Cloudera

Re: Problems connecting form Spark

[Mac Noland]

Any chance you can try spark2-shell with Kudu 1.6 and then re-try your
tests?

spark-shell --packages org.apache.kudu:kudu-spark2_2.11:1.6.0

On Fri, Mar 2, 2018 at 5:02 AM, Saúl Nogueras  wrote:

> I cannot properly connect to Kudu from Spark, error says “Kudu master has
> no leader”
>
>- CDH 5.14
>- Kudu 1.6
>- Spark 1.6.0 standalone and 2.2.0
>
> When I use Impala in HUE to create and query kudu tables, it works
> flawlessly.
>
> However, connecting from Spark throws some errors I cannot decipher.
>
> I have tried using both pyspark and spark-shell. With spark shell I had to
> use spark 1.6 instead of 2.2 because some maven dependencies problems, that
> I have localized but not been able to fix. More info here.
> --
> Case 1: using pyspark2 (Spark 2.2.0)
>
> $ pyspark2 --master yarn --jars 
> /opt/cloudera/parcels/CDH-5.14.0-1.cdh5.14.0.p0.24/lib/kudu/kudu-spark2_2.11.jar
>
> > df = 
> > sqlContext.read.format('org.apache.kudu.spark.kudu').options(**{"kudu.master":"172.17.0.43:7077",
> >  "kudu.table":"impala::default.test"}).load()
>
> 18/03/02 10:23:27 WARN client.ConnectToCluster: Error receiving response from 
> 172.17.0.43:7077
> org.apache.kudu.client.RecoverableException: [peer master-172.17.0.43:7077] 
> encountered a read timeout; closing the channel
> at 
> org.apache.kudu.client.Connection.exceptionCaught(Connection.java:412)
> at 
> org.apache.kudu.shaded.org.jboss.netty.channel.SimpleChannelUpstreamHandler.handleUpstream(SimpleChannelUpstreamHandler.java:112)
> at 
> org.apache.kudu.client.Connection.handleUpstream(Connection.java:239)
> at 
> org.apache.kudu.shaded.org.jboss.netty.channel.DefaultChannelPipeline.sendUpstream(DefaultChannelPipeline.java:564)
> at 
> org.apache.kudu.shaded.org.jboss.netty.channel.DefaultChannelPipeline$DefaultChannelHandlerContext.sendUpstream(DefaultChannelPipeline.java:791)
> at 
> org.apache.kudu.shaded.org.jboss.netty.channel.SimpleChannelUpstreamHandler.exceptionCaught(SimpleChannelUpstreamHandler.java:153)
> at 
> org.apache.kudu.shaded.org.jboss.netty.channel.SimpleChannelUpstreamHandler.handleUpstream(SimpleChannelUpstreamHandler.java:112)
> at 
> org.apache.kudu.shaded.org.jboss.netty.channel.DefaultChannelPipeline.sendUpstream(DefaultChannelPipeline.java:564)
> at 
> org.apache.kudu.shaded.org.jboss.netty.channel.DefaultChannelPipeline$DefaultChannelHandlerContext.sendUpstream(DefaultChannelPipeline.java:791)
> at 
> org.apache.kudu.shaded.org.jboss.netty.channel.Channels.fireExceptionCaught(Channels.java:536)
> at 
> org.apache.kudu.shaded.org.jboss.netty.handler.timeout.ReadTimeoutHandler.readTimedOut(ReadTimeoutHandler.java:236)
> at 
> org.apache.kudu.shaded.org.jboss.netty.handler.timeout.ReadTimeoutHandler$ReadTimeoutTask$1.run(ReadTimeoutHandler.java:276)
> at 
> org.apache.kudu.shaded.org.jboss.netty.channel.socket.ChannelRunnableWrapper.run(ChannelRunnableWrapper.java:40)
> at 
> org.apache.kudu.shaded.org.jboss.netty.channel.socket.nio.AbstractNioSelector.processTaskQueue(AbstractNioSelector.java:391)
> at 
> org.apache.kudu.shaded.org.jboss.netty.channel.socket.nio.AbstractNioSelector.run(AbstractNioSelector.java:315)
> at 
> org.apache.kudu.shaded.org.jboss.netty.channel.socket.nio.AbstractNioWorker.run(AbstractNioWorker.java:89)
> at 
> org.apache.kudu.shaded.org.jboss.netty.channel.socket.nio.NioWorker.run(NioWorker.java:178)
> at 
> org.apache.kudu.shaded.org.jboss.netty.util.ThreadRenamingRunnable.run(ThreadRenamingRunnable.java:108)
> at 
> org.apache.kudu.shaded.org.jboss.netty.util.internal.DeadLockProofWorker$1.run(DeadLockProofWorker.java:42)
> at 
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at 
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> at java.lang.Thread.run(Thread.java:748)
> Caused by: 
> org.apache.kudu.shaded.org.jboss.netty.handler.timeout.ReadTimeoutException
> at 
> org.apache.kudu.shaded.org.jboss.netty.handler.timeout.ReadTimeoutHandler.(ReadTimeoutHandler.java:84)
> at 
> org.apache.kudu.client.Connection$ConnectionPipeline.init(Connection.java:782)
> at org.apache.kudu.client.Connection.(Connection.java:199)
> at 
> org.apache.kudu.client.ConnectionCache.getConnection(ConnectionCache.java:133)
> at 
> org.apache.kudu.client.AsyncKuduClient.newRpcProxy(AsyncKuduClient.java:248)
> at 
> org.apache.kudu.client.AsyncKuduClient.newMasterRpcProxy(AsyncKuduClient.java:272)
> at 
> org.apache.kudu.client.ConnectToCluster.run(ConnectToCluster.java:157)
> at 
> org.apache.kudu.client.AsyncKuduClient.getMasterTableLocationsPB(AsyncKuduClient.java:1350)
> at 
> org.apache.kudu.client.AsyncKuduClient.exportAuthenticationCredentials(AsyncKuduClient.java:651)
>   

Re: Kudu as a Graphite backend

[Paul Brannan]

Do you want to use kudu as a backend for carbon (i.e. have graphite/carbon
receive metrics and write them to kudu), or do you want to use graphite-web
as a frontend for timeseries you already have in kudu?  Both are mostly
straightforward; see e.g.
https://github.com/criteo/biggraphite/tree/master/biggraphite/plugins for
an example of each.  AFAICT the examples (
https://github.com/cloudera/kudu-examples/tree/master/python/graphite-kudu)
are just a graphite-web finder; you'd still need a carbon backend for
storage, unless you insert the data through a different mechanism.

On Mon, Mar 5, 2018 at 6:15 AM, Mark Meyer  wrote:

> Hi List,
> has anybody experiences running Kudu as a Graphite backend in production?
> I've been looking at the samples repository, but have been unsure,
> primarily because of the 'samples' tag associated with the code.
>
> Best, Mark
>
> --
> Mark Meyer
> Systems Engineer
> mark.me...@smaato.com
> Smaato Inc.
> San Francisco – New York – Hamburg – Singapore
> www.smaato.com
>
> Valentinskamp 70
> ,
> Emporio, 19th Floor
> 20355 Hamburg
> T: ­0049 (40) 3480 949 0
> F: 0049 (40) 492 19 055
>
> The information contained in this communication may be CONFIDENTIAL and is
> intended only for the use of the recipient(s) named above. If you are not
> the intended recipient, you are hereby notified that any dissemination,
> distribution, or copying of this communication, or any of its contents, is
> strictly prohibited. If you have received this communication in error,
> please notify the sender and delete/destroy the original message and any
> copy of it from your computer or paper files.
>

Kudu as a Graphite backend

[Mark Meyer]

Hi List,
has anybody experiences running Kudu as a Graphite backend in production?
I've been looking at the samples repository, but have been unsure,
primarily because of the 'samples' tag associated with the code.

Best, Mark

-- 
Mark Meyer
Systems Engineer
mark.me...@smaato.com
Smaato Inc.
San Francisco – New York – Hamburg – Singapore
www.smaato.com

Valentinskamp 70, Emporio, 19th Floor
20355 Hamburg
T: ­0049 (40) 3480 949 0
F: 0049 (40) 492 19 055

The information contained in this communication may be CONFIDENTIAL and is
intended only for the use of the recipient(s) named above. If you are not
the intended recipient, you are hereby notified that any dissemination,
distribution, or copying of this communication, or any of its contents, is
strictly prohibited. If you have received this communication in error,
please notify the sender and delete/destroy the original message and any
copy of it from your computer or paper files.